Correct operator usage

I'm using IPUMS CPS data and created a binary variable for disability from the six different variables within IPUMS for disability (https://cps.ipums.org/cps-action/variables/group/core_dis)

bias <- bias %>%
  mutate(DISABLED= if_else(.$DIFFCARE ==2|
                           .$DIFFMOB == 2 |
                           .$DIFFEYE ==2 |
                           .$DIFFREM == 2 |
                           .$DIFFPHYS == 2|
                           .$DIFFMOB == 2 |
                           .$DIFFCARE ==2 |
                           .$DIFFANY == 2|
                           .$DIFFHEAR == 2,1, 0))

If the respondent replied yes to any of the various disabilities, they were categorized under the new "Disabled" variable above with a "1". For not disabled, I'm looking for survey respondents to have selected "no disability" among the six variables. I believe the DISABLED code above, when coded as "0," may signify they only had categorized as not having a disability in one or more of the disability categories; however, I need them to be not disabled in all the categories.

So, I created this variable below, but I'm not sure this captures what I want.

bias <- bias %>%
  mutate(NOTDISABLED= if_else(.$DIFFCARE == 1|
                              .$DIFFMOB == 1 |
                              .$DIFFEYE == 1 |
                              .$DIFFREM == 1 |
                              .$DIFFPHYS == 1|
                              .$DIFFMOB == 1 |
                              .$DIFFCARE == 1 |
                              .$DIFFANY == 1|
                              .$DIFFHEAR == 1, 1, 0))

Please advise. Thank you again for reading!

As Sirius said, the key is using &:

bias <- bias %>%
  mutate(NOTDISABLED= if_else(DIFFCARE == 1|
                              DIFFMOB == 1 |
                              DIFFEYE == 1 |
                              DIFFREM == 1 |
                              DIFFPHYS == 1|
                              DIFFMOB == 1 |
                              DIFFCARE == 1 |
                              DIFFANY == 1|
                              DIFFHEAR == 1, 1, 0),
        DISABLED= if_else(DIFFCARE == 1 &
                              DIFFMOB == 1 &
                              DIFFEYE == 1 &
                              DIFFREM == 1 &
                              DIFFPHYS == 1 &
                              DIFFMOB == 1 &
                              DIFFCARE == 1 &
                              DIFFANY == 1 &
                              DIFFHEAR == 1, 1, 0))

Code simplified (removed .$s, they are unnecessary). See the documentation for more information on things like & and | (Boolean operators)

You can avoid the multiple ifelse statements like this:

suppressPackageStartupMessages(library(tidyverse))

bias <- data.frame(id = 1:5,
                   DIFFCARE  = c(0,0,0,0,0),
                   DIFFMOB   = c(0,0,1,0,0),
                   DIFFEYE   = c(0,1,0,0,0),
                   DIFFREM   = c(0,0,0,0,1), 
                   DIFFPHYS  = c(0,0,0,0,0),
                   DIFFANY   = c(0,0,0,0,0),
                   DIFFHEAR  = c(0,0,1,0,0))
bias %>%
  mutate(diffsum = rowSums(across(contains("DIFF"))),
         Disabled = ifelse(diffsum == 0, "No", "Yes"))
#>   id DIFFCARE DIFFMOB DIFFEYE DIFFREM DIFFPHYS DIFFANY DIFFHEAR diffsum
#> 1  1        0       0       0       0        0       0        0       0
#> 2  2        0       0       1       0        0       0        0       1
#> 3  3        0       1       0       0        0       0        1       2
#> 4  4        0       0       0       0        0       0        0       0
#> 5  5        0       0       0       1        0       0        0       1
#>   Disabled
#> 1       No
#> 2      Yes
#> 3      Yes
#> 4       No
#> 5      Yes

^{Created on 2023-06-26 with reprex v2.0.2}